Bibliographic record
Abstract
Abstract. According to the rational choice model, the calculus of voting takes the form of the equation R = BP − C, where the net rewards for voting (R) are a function of the instrumental benefits from the preferred outcome compared to others (B) and the probability (P) of casting the decisive vote that secures these benefits, minus the costs of becoming informed and going to the polls (C). Here, we provide a systematic test of this model. The analysis relies on two surveys, conducted during the 1995 Quebec referendum and the 1996 British Columbia provincial election, in which very specific questions measured each element of the model. As well, this study incorporates two other factors that can affect the propensity to vote — Respondents’ level of political interest and their sense of duty. We find that B, P, and C each matter, but only among those with a relatively weak sense of duty. The feeling that one has a moral obligation to vote is the most powerful motivation to go to the polls. We conclude that the rational choice model is useful, but only in explaining behaviour at the margins of this important norm.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.036 | 0.184 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.009 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.031 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".